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Sub-seasonal to Seasonal Prediction – eBook PDF


eBook details

  • Authors: Andrew Robertson, Frederic Vitart
  • File Size: 52 MB
  • Format: PDF
  • Length: 550 pages
  • Publisher: Elsevier
  • Publication Date: October 19, 2018
  • Language: English
  • ASIN: B07JQN2ZQ7
  • ISBN-10: 0128117141
  • ISBN-13: 9780128117149, 9780128117156


Sub-seasonal to Seasonal Prediction: The Gap Between Weather and Climate Forecasting – eBook PDF

The Gap Between Weather and Climate Forecasting: Sub-seasonal to Seasonal Prediction (PDF) is an ideal reference for practitioners and researchers across the range of disciplines involved in the modeling, science, forecasting and application of this new frontier in sub-seasonal to seasonal (S2S) prediction. It provides an accessible, yet rigorous, introduction to the scientific principles and sources of predictability through the unique challenges of numerical simulation and forecasting with state-of-science modelling codes and supercomputers. Additional coverage includes the prospects for developing applications to trigger early action decisions to lessen weather catastrophes, minimize costly damage, and optimize operator decisions.

The ebook consists of a set of contributed chapters solicited from experts and leaders in the fields of S2S predictability science, numerical modeling, operational forecasting, and developing application sectors. The introduction and conclusion, written by the co-editors, provides historical perspective, unique synthesis and prospects, and emerging opportunities in this exciting, complex and interdisciplinary field.

  • Includes a broad set of topics, illustrated with graphic examples, that highlight interdisciplinary linkages
  • Contains contributed chapters from leaders and experts in sub-seasonal to seasonal science, forecasting and applications
  • Provides a one-stop-shop for academic and applied researchers, graduate students, and practitioners in an emerging and interdisciplinary field
  • Offers a synthesis of the state of S2S science through the use of concrete examples, enabling potential users of S2S forecasts to quickly grasp the potential for application in their own decision-making


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